Josh Dillon, Last Revised January 2022
This notebook examines an individual antenna's performance over a whole season. This notebook parses information from each nightly rtp_summarynotebook (as saved to .csvs) and builds a table describing antenna performance. It also reproduces per-antenna plots from each auto_metrics notebook pertinent to the specific antenna.
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))
# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "004"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder
# Use environment variables to figure out path to the csvs and auto_metrics
antenna = str(int(os.environ["ANTENNA"]))
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')
antenna = "159" csv_folder = "/home/obs/src/H6C_Notebooks/_rtp_summary_" auto_metrics_folder = "/home/obs/src/H6C_Notebooks/auto_metrics_inspect"
display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))
import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna
# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, 'rtp_summary_table*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')
Found 91 csvs in /home/obs/src/H6C_Notebooks/_rtp_summary_ Found 89 auto_metrics notebooks in /home/obs/src/H6C_Notebooks/auto_metrics_inspect
# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0
def jd_to_summary_url(jd):
return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'
def jd_to_auto_metrics_url(jd):
return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'
this_antenna = None
jds = []
# parse information about antennas and nodes
for csv in csvs:
df = pd.read_csv(csv)
for n in range(len(df)):
# Add this day to the antenna
row = df.loc[n]
if isinstance(row['Ant'], str) and '<a href' in row['Ant']:
antnum = int(row['Ant'].split('</a>')[0].split('>')[-1]) # it's a link, extract antnum
else:
antnum = int(row['Ant'])
if antnum != int(antenna):
continue
if np.issubdtype(type(row['Node']), np.integer):
row['Node'] = str(row['Node'])
if type(row['Node']) == str and row['Node'].isnumeric():
row['Node'] = 'N' + ('0' if len(row['Node']) == 1 else '') + row['Node']
if this_antenna is None:
this_antenna = Antenna(row['Ant'], row['Node'])
jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
jds.append(jd)
this_antenna.add_day(jd, row)
break
# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]
df = pd.DataFrame(to_show)
# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
df[col] = bar_cols[col]
z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
df[col] = z_score_cols[col]
ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
df[col] = ant_metrics_cols[col]
redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]
for col in redcal_cols:
df[col] = redcal_cols[col]
# style dataframe
table = df.style.hide_index()\
.applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
.background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
.background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
.background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
.background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
.applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
.applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
.applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
.applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
.bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
.format({col: '{:,.4f}'.format for col in z_score_cols}) \
.format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
.format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
.set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])
This table reproduces each night's row for this antenna from the RTP Summary notebooks. For more info on the columns, see those notebooks, linked in the JD column.
display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))
| JDs | A Priori Status | Auto Metrics Flags | Dead Fraction in Ant Metrics (Jee) | Dead Fraction in Ant Metrics (Jnn) | Crossed Fraction in Ant Metrics | Flag Fraction Before Redcal | Flagged By Redcal chi^2 Fraction | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | Average Dead Ant Metric (Jee) | Average Dead Ant Metric (Jnn) | Average Crossed Ant Metric | Median chi^2 Per Antenna (Jee) | Median chi^2 Per Antenna (Jnn) |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2459908 | RF_maintenance | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 0.152494 | 22.412837 | -1.515353 | -1.016643 | -1.490207 | 4.638152 | -0.074339 | 60.673258 | 0.6400 | 0.5869 | 0.3780 | nan | nan |
| 2459907 | RF_maintenance | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 0.120013 | 28.555847 | -1.617811 | -0.942207 | -1.313492 | 2.088518 | -0.350012 | 22.448194 | 0.6352 | 0.5445 | 0.3670 | nan | nan |
| 2459906 | RF_maintenance | 100.00% | 0.00% | 0.00% | 0.00% | - | - | -0.000180 | 20.081255 | -1.279207 | -1.039358 | -1.344523 | 6.083433 | -0.411757 | 25.165954 | 0.6275 | 0.5857 | 0.3804 | nan | nan |
| 2459905 | RF_maintenance | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 0.075833 | 23.792732 | -1.429550 | -0.925242 | -2.141755 | 10.523693 | -0.255220 | 39.994573 | 0.6087 | 0.5408 | 0.3798 | nan | nan |
| 2459904 | RF_maintenance | 100.00% | 0.00% | 0.00% | 0.00% | - | - | -0.081539 | 30.176818 | -1.305750 | -0.672633 | -1.017044 | 3.140048 | 0.000267 | 0.626796 | 0.6125 | 0.5057 | 0.3635 | nan | nan |
| 2459903 | RF_maintenance | 100.00% | 0.00% | 0.00% | 0.00% | - | - | -0.051009 | 16.356403 | -1.514935 | -1.156706 | -1.419908 | 5.782532 | 0.104296 | 7.855364 | 0.6161 | 0.5928 | 0.3881 | nan | nan |
| 2459902 | RF_maintenance | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 0.149514 | 30.693492 | -1.432132 | -0.839542 | -1.295293 | 5.007622 | -0.084039 | 29.136345 | 0.6224 | 0.5339 | 0.3677 | nan | nan |
| 2459901 | RF_maintenance | 100.00% | 0.00% | 0.00% | 0.00% | - | - | -0.129639 | 27.865032 | -1.685507 | -1.076585 | -1.353676 | 4.818527 | -0.428075 | 46.028952 | 0.6407 | 0.5519 | 0.3725 | nan | nan |
| 2459900 | RF_maintenance | 100.00% | 0.00% | 0.00% | 0.00% | - | - | -0.474531 | 23.951372 | -1.709360 | -1.104126 | -0.893384 | 8.940257 | -0.443982 | 23.799981 | 0.5812 | 0.5113 | 0.3095 | nan | nan |
| 2459898 | RF_maintenance | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 0.020273 | 17.879625 | -1.620917 | -1.228749 | -1.589464 | 7.950244 | 0.149782 | 5.509785 | 0.6316 | 0.5872 | 0.3789 | nan | nan |
| 2459897 | RF_maintenance | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 0.098663 | 28.352735 | -1.267047 | -0.761767 | -1.225770 | 2.553900 | -0.228039 | 1.825711 | 0.6299 | 0.5076 | 0.3726 | nan | nan |
| 2459896 | RF_maintenance | 100.00% | 0.00% | 0.00% | 0.00% | - | - | -0.092347 | 27.763910 | -1.427469 | -0.802202 | -2.049235 | 2.918533 | -0.001124 | 1.855945 | 0.6315 | 0.5101 | 0.3710 | nan | nan |
| 2459895 | RF_maintenance | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 0.120871 | 32.096685 | -1.688926 | -0.852633 | -1.510431 | 2.446577 | -1.890847 | 0.600901 | 0.7189 | 0.6008 | 0.2691 | nan | nan |
| 2459894 | RF_maintenance | 100.00% | 0.00% | 0.00% | 0.00% | - | - | -0.072346 | 32.999204 | -1.262112 | -0.793764 | -1.412783 | 3.710095 | -0.332471 | 6.688827 | 0.6329 | 0.5101 | 0.3663 | nan | nan |
| 2459893 | RF_maintenance | 100.00% | 0.00% | 0.00% | 0.00% | - | - | -0.270923 | 33.589366 | -1.531754 | -0.866083 | -1.280226 | 3.176147 | 0.969814 | 4.065029 | 0.6422 | 0.5245 | 0.3632 | nan | nan |
| 2459892 | RF_maintenance | 100.00% | 0.00% | 0.00% | 0.00% | - | - | -0.120524 | 33.685419 | -1.738048 | -0.959369 | -1.997663 | 2.341912 | -0.271044 | 1.230786 | 0.6423 | 0.5213 | 0.3607 | nan | nan |
| 2459891 | RF_maintenance | 100.00% | 0.00% | 0.00% | 0.00% | - | - | -0.194498 | 31.140657 | -1.410472 | -0.833006 | -2.025420 | 3.794921 | -0.416722 | 0.392945 | 0.6358 | 0.5133 | 0.3629 | nan | nan |
| 2459890 | RF_maintenance | 100.00% | 0.00% | 0.00% | 0.00% | - | - | -0.030615 | 26.895369 | -2.007642 | -1.229685 | -1.169369 | 8.410837 | -0.351021 | 16.003204 | 0.6353 | 0.5328 | 0.3634 | nan | nan |
| 2459889 | RF_maintenance | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 0.017660 | 20.002378 | -1.460974 | -1.380889 | -1.883275 | 10.977406 | -0.014486 | 8.629977 | 0.6437 | 0.5935 | 0.3752 | nan | nan |
| 2459888 | RF_maintenance | 100.00% | 0.00% | 0.00% | 0.00% | - | - | -0.015359 | 24.921056 | -1.781785 | -1.094170 | -1.603721 | 8.263861 | -0.787364 | 5.930731 | 0.6591 | 0.5777 | 0.3639 | nan | nan |
| 2459887 | RF_maintenance | 100.00% | 0.00% | 0.00% | 0.00% | - | - | -0.041788 | 28.375917 | -2.354668 | -1.420304 | -2.192718 | 2.863040 | -0.205519 | 0.800181 | 0.6448 | 0.5377 | 0.3664 | nan | nan |
| 2459886 | RF_maintenance | 100.00% | 0.00% | 0.00% | 0.00% | - | - | -0.188308 | 33.547584 | -1.648721 | -0.916774 | -2.282599 | 1.318885 | -1.654820 | -0.325543 | 0.7246 | 0.6269 | 0.3267 | nan | nan |
| 2459885 | RF_maintenance | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 2.275686 | 42.933182 | 10.777221 | 10.285617 | 1.307766 | 12.492708 | 4.483958 | 14.528052 | 0.6824 | 0.5703 | 0.3433 | nan | nan |
| 2459884 | RF_maintenance | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 1.172737 | 22.475564 | 2.467395 | 1.340175 | 0.739960 | 3.791275 | -1.808848 | 7.191314 | 0.6769 | 0.5420 | 0.3765 | nan | nan |
| 2459883 | RF_maintenance | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 2.986347 | 29.334931 | 29.353912 | 25.687535 | 2.586344 | 6.289794 | -2.886254 | 8.453725 | 0.6684 | 0.5416 | 0.3655 | nan | nan |
| 2459882 | RF_maintenance | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 4.069873 | 51.362316 | 34.488373 | 29.457915 | 2.795653 | 9.327820 | -1.135393 | 11.850156 | 0.6668 | 0.5338 | 0.3722 | nan | nan |
| 2459881 | RF_maintenance | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 2.804564 | 29.406272 | 38.680092 | 32.975841 | 7.294977 | 18.393634 | -2.387920 | 6.991780 | 0.7155 | 0.6136 | 0.3143 | nan | nan |
| 2459880 | RF_maintenance | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 2.950771 | 35.020742 | 30.938884 | 27.218199 | 1.977666 | 6.887256 | -1.741270 | 15.800915 | 0.6680 | 0.5405 | 0.3747 | nan | nan |
| 2459879 | RF_maintenance | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 0.210771 | 19.948113 | -0.090668 | -1.073717 | -2.029038 | -0.095054 | -1.357993 | 1.414326 | 0.6527 | 0.5326 | 0.3852 | nan | nan |
| 2459878 | RF_maintenance | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 3.068536 | 29.717045 | 37.865309 | 34.161660 | 3.635748 | 10.365673 | -1.950188 | 37.857320 | 0.6637 | 0.5526 | 0.3800 | nan | nan |
| 2459876 | RF_maintenance | 100.00% | 100.00% | 100.00% | 0.00% | - | - | nan | nan | inf | inf | nan | nan | nan | nan | nan | nan | nan | nan | nan |
| 2459875 | RF_maintenance | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 2.799543 | 37.100992 | 36.513614 | 30.772664 | 4.423075 | 12.709159 | -0.704371 | 3.656526 | 0.6993 | 0.5701 | 0.3571 | nan | nan |
| 2459874 | RF_maintenance | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 4.173398 | 50.970943 | 18.769595 | 15.701239 | 5.695385 | 15.143364 | -2.245827 | -1.919733 | 0.6908 | 0.5332 | 0.3595 | nan | nan |
| 2459873 | RF_maintenance | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 2.579334 | 41.376401 | 25.322557 | 20.790276 | 1.829200 | 7.312243 | -1.979578 | -0.818346 | 0.6933 | 0.5261 | 0.3572 | nan | nan |
auto_metrics notebooks.¶htmls_to_display = []
for am_html in auto_metric_htmls:
html_to_display = ''
# read html into a list of lines
with open(am_html) as f:
lines = f.readlines()
# find section with this antenna's metric plots and add to html_to_display
jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
try:
section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
except ValueError:
continue
html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
for line in lines[section_start_line + 1:]:
html_to_display += line
if '<hr' in line:
htmls_to_display.append(html_to_display)
break
These figures are reproduced from auto_metrics notebooks. For more info on the specific plots and metrics, see those notebooks (linked at the JD). The most recent 100 days (at most) are shown.
for i, html_to_display in enumerate(htmls_to_display):
if i == 100:
break
display(HTML(html_to_display))
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 159 | N13 | RF_maintenance | nn Temporal Discontinuties | 60.673258 | 0.152494 | 22.412837 | -1.515353 | -1.016643 | -1.490207 | 4.638152 | -0.074339 | 60.673258 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 159 | N13 | RF_maintenance | nn Shape | 28.555847 | 28.555847 | 0.120013 | -0.942207 | -1.617811 | 2.088518 | -1.313492 | 22.448194 | -0.350012 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 159 | N13 | RF_maintenance | nn Temporal Discontinuties | 25.165954 | 20.081255 | -0.000180 | -1.039358 | -1.279207 | 6.083433 | -1.344523 | 25.165954 | -0.411757 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 159 | N13 | RF_maintenance | nn Temporal Discontinuties | 39.994573 | 23.792732 | 0.075833 | -0.925242 | -1.429550 | 10.523693 | -2.141755 | 39.994573 | -0.255220 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 159 | N13 | RF_maintenance | nn Shape | 30.176818 | 30.176818 | -0.081539 | -0.672633 | -1.305750 | 3.140048 | -1.017044 | 0.626796 | 0.000267 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 159 | N13 | RF_maintenance | nn Shape | 16.356403 | 16.356403 | -0.051009 | -1.156706 | -1.514935 | 5.782532 | -1.419908 | 7.855364 | 0.104296 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 159 | N13 | RF_maintenance | nn Shape | 30.693492 | 0.149514 | 30.693492 | -1.432132 | -0.839542 | -1.295293 | 5.007622 | -0.084039 | 29.136345 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 159 | N13 | RF_maintenance | nn Temporal Discontinuties | 46.028952 | -0.129639 | 27.865032 | -1.685507 | -1.076585 | -1.353676 | 4.818527 | -0.428075 | 46.028952 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 159 | N13 | RF_maintenance | nn Shape | 23.951372 | -0.474531 | 23.951372 | -1.709360 | -1.104126 | -0.893384 | 8.940257 | -0.443982 | 23.799981 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 159 | N13 | RF_maintenance | nn Shape | 17.879625 | 17.879625 | 0.020273 | -1.228749 | -1.620917 | 7.950244 | -1.589464 | 5.509785 | 0.149782 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 159 | N13 | RF_maintenance | nn Shape | 28.352735 | 28.352735 | 0.098663 | -0.761767 | -1.267047 | 2.553900 | -1.225770 | 1.825711 | -0.228039 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 159 | N13 | RF_maintenance | nn Shape | 27.763910 | 27.763910 | -0.092347 | -0.802202 | -1.427469 | 2.918533 | -2.049235 | 1.855945 | -0.001124 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 159 | N13 | RF_maintenance | nn Shape | 32.096685 | 0.120871 | 32.096685 | -1.688926 | -0.852633 | -1.510431 | 2.446577 | -1.890847 | 0.600901 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 159 | N13 | RF_maintenance | nn Shape | 32.999204 | 32.999204 | -0.072346 | -0.793764 | -1.262112 | 3.710095 | -1.412783 | 6.688827 | -0.332471 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 159 | N13 | RF_maintenance | nn Shape | 33.589366 | -0.270923 | 33.589366 | -1.531754 | -0.866083 | -1.280226 | 3.176147 | 0.969814 | 4.065029 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 159 | N13 | RF_maintenance | nn Shape | 33.685419 | 33.685419 | -0.120524 | -0.959369 | -1.738048 | 2.341912 | -1.997663 | 1.230786 | -0.271044 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 159 | N13 | RF_maintenance | nn Shape | 31.140657 | -0.194498 | 31.140657 | -1.410472 | -0.833006 | -2.025420 | 3.794921 | -0.416722 | 0.392945 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 159 | N13 | RF_maintenance | nn Shape | 26.895369 | 26.895369 | -0.030615 | -1.229685 | -2.007642 | 8.410837 | -1.169369 | 16.003204 | -0.351021 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 159 | N13 | RF_maintenance | nn Shape | 20.002378 | 0.017660 | 20.002378 | -1.460974 | -1.380889 | -1.883275 | 10.977406 | -0.014486 | 8.629977 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 159 | N13 | RF_maintenance | nn Shape | 24.921056 | 24.921056 | -0.015359 | -1.094170 | -1.781785 | 8.263861 | -1.603721 | 5.930731 | -0.787364 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 159 | N13 | RF_maintenance | nn Shape | 28.375917 | 28.375917 | -0.041788 | -1.420304 | -2.354668 | 2.863040 | -2.192718 | 0.800181 | -0.205519 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 159 | N13 | RF_maintenance | nn Shape | 33.547584 | -0.188308 | 33.547584 | -1.648721 | -0.916774 | -2.282599 | 1.318885 | -1.654820 | -0.325543 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 159 | N13 | RF_maintenance | nn Shape | 42.933182 | 42.933182 | 2.275686 | 10.285617 | 10.777221 | 12.492708 | 1.307766 | 14.528052 | 4.483958 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 159 | N13 | RF_maintenance | nn Shape | 22.475564 | 22.475564 | 1.172737 | 1.340175 | 2.467395 | 3.791275 | 0.739960 | 7.191314 | -1.808848 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 159 | N13 | RF_maintenance | ee Power | 29.353912 | 29.334931 | 2.986347 | 25.687535 | 29.353912 | 6.289794 | 2.586344 | 8.453725 | -2.886254 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 159 | N13 | RF_maintenance | nn Shape | 51.362316 | 51.362316 | 4.069873 | 29.457915 | 34.488373 | 9.327820 | 2.795653 | 11.850156 | -1.135393 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 159 | N13 | RF_maintenance | ee Power | 38.680092 | 29.406272 | 2.804564 | 32.975841 | 38.680092 | 18.393634 | 7.294977 | 6.991780 | -2.387920 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 159 | N13 | RF_maintenance | nn Shape | 35.020742 | 35.020742 | 2.950771 | 27.218199 | 30.938884 | 6.887256 | 1.977666 | 15.800915 | -1.741270 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 159 | N13 | RF_maintenance | nn Shape | 19.948113 | 19.948113 | 0.210771 | -1.073717 | -0.090668 | -0.095054 | -2.029038 | 1.414326 | -1.357993 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 159 | N13 | RF_maintenance | ee Power | 37.865309 | 29.717045 | 3.068536 | 34.161660 | 37.865309 | 10.365673 | 3.635748 | 37.857320 | -1.950188 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 159 | N13 | RF_maintenance | ee Shape | nan | nan | nan | inf | inf | nan | nan | nan | nan |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 159 | N13 | RF_maintenance | nn Shape | 37.100992 | 2.799543 | 37.100992 | 36.513614 | 30.772664 | 4.423075 | 12.709159 | -0.704371 | 3.656526 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 159 | N13 | RF_maintenance | nn Shape | 50.970943 | 4.173398 | 50.970943 | 18.769595 | 15.701239 | 5.695385 | 15.143364 | -2.245827 | -1.919733 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 159 | N13 | RF_maintenance | nn Shape | 41.376401 | 2.579334 | 41.376401 | 25.322557 | 20.790276 | 1.829200 | 7.312243 | -1.979578 | -0.818346 |